Recent work in RF-based imaging has demonstrated the capacity for real-time or near-real-time high resolution imaging using millmeter wave rader (mm-wave) radar. Others have focused on extracting Doppler information from lower frequency wireless signals already readily available, such as over-the-air TV transmission or in-home WIFI signals, enabling the recognition and classification of gestures. Micro-Doppler analysis has been applied to the problems of target recognition and activity classification on a larger scale at distances of up to 50 meters using mm-wave radar systems. These classification systems are typically based on a preprocessing step which extracts a feature vector and a support vector machine which classifies the feature vector by dividing the feature volume into regions corresponding to different labels.
Hidden Markov Models (HMMs) present a distinct approach to classification by assuming that the observations are related to an unobserved dynamic system process, with statistics that may change as a function of the unobservable system state. The objective, then, is to estimate the sequence of states that provides the best statistical explanation of the observed data. The use of HMMs for gesture recognition in imager video-processing based systems is widespread, but they have not yet been applied to radar-based recognition systems.
In this invention, we apply micro-Doppler analysis to measurements obtained with a Frequency Modulated Continuous Wave (FMCW) radar system operating at 77 GHz in order to perform gesture recognition and classification using a Hidden Markov Model. As shown in FIG. 1, a radar based recognition system may include an RF transmitter and receiver (102), a transmit/receive antenna (103) and a signal processing unit (101). A feature extraction algorithm is also shown that offers a significant reduction of feature vector dimension while preserving recognition performance using test data. A mm-wave radar system used for gesture detection gains all of the benefits of imaging radar, creating a significant advantage over a camera based system or one that operates passively using background signals.